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Background Differential diagnosis of single-nodule pulmonary metastasis (SNPM) and second primary lung cancer (SPLC) in patients with colorectal cancer (CRC) prior to lung surgery is relatively complex. Radiomics is an emerging technique for image information analysis, while it has not yet been applied to construct a differential diagnostic model between SNPM and SPLC in patients with CRC. In the present study, we aimed to extract radiomics signatures from thin-section computed tomography (CT) images of the chest. These radiomics signatures were combined with clinical features to construct a composite differential diagnostic model. Method A total of 91 patients with CRC, including 66 patients with SNPM and 25 patients with SPLC, were enrolled in this study. Patients were randomly assigned to the training cohort (n = 63) and validation cohort (n = 28) at a ratio of 7 to 3. Moreover, 107 radiomics features were extracted from the chest thin-section CT images. The least absolute shrinkage and selection operator (LASSO) regression was used to filter these features, and clinical features were screened by univariate analysis. The screened radiomics and clinical features were combined to construct a multifactorial logistic regression composite model. The receiver operating characteristic (ROC) curves were adopted to evaluate the models, and the corresponding nomograms were created. Results A series of 6 radiomics characteristics was screened by LASSO. After univariate logistic regression analysis, the composite model finally included 4 radiomics features and 4 clinical features. In the training cohort, the area under the curve scores of ROC curves were 0.912 (95% confidence interval [CI]: 0.813-0.969), 0.884 (95% CI: 0.778-0.951), and 0.939 (95% CI: 0.848-0.984) for models derived from radiomics, clinical, and combined features, respectively. Similarly, these values were 0.756 (95% CI: 0.558-0.897), 0.888 (95% CI: 0.711-0.975), and 0.950 (95% CI: 0.795-0.997) in the validation cohort, respectively. Conclusions We constructed a model for differential diagnosis of SNPM and SPLC in patients with CRC using radiomics and clinical features. Moreover, our findings provided a new assessment tool for patients with CRC in the future.

Objective: To explore the effect and the related mechanism of STAT3 inhibitor AG-490 on inhibiting the proliferation of prostate cancer cells. Methods: PC3 cells and DU145 cells were cultured stably and treated with AG-490 to detect the changes in the activity of PC3 cells and DU145 cells. Thirty 6-8 weeks male BALB/c nude mouse were randomly divided into a control group, a DMSO group, and an AG-490 group to detect differences in various indexes . Results: The overexpression of miR-503-5p depends on the activation of STAT3. After treatment with AG-490, The proliferation and invasion of PC3 cells and DU145 cells and the expression of miR-503-5p were all reduced. Luciferase reporter assay demonstrated that the target proteins of miR-503-5p include PDCD4, TIMP-3, and PTEN. After treatment with AG-490, the expression of PDCD4, TIMP-3, and PTEN in cells was significantly up-regulated. IL-6-induced overexpression of miR-503-5p and restored the expression of STAT3, demonstrating the correlation between STAT3 and miR-503-5p. AG-490 can inhibit tumor growth and induce tumor cell apoptosis in the PC3 BALB/c nude mouse xenograft model. Western blotting and immunohistochemical staining showed that the expression levels of STAT3, Ki67, Bcl-2 and MMP-2 in the AG-490 group were significantly reduced, and the expression of PDCD4, TIMP-3 and PTEN increased. Conclusion: AG-490 can inhibit the growth of prostate cancer cells in a miR-503-5p-dependent manner by targeting STAT3. AG-490 is expected to become a new candidate drug for the treatment of prostate cancer.

Background: Pancreatic cancer is an aggressive type of cancer with poor prognosis, short survival rate, and high mortality. Drug resistance is a major cause of treatment failure in the disease. MiR-331-3p has been reported to play an important role in several cancers. We previously showed that miR-331-3p is upregulated in pancreatic cancer and promotes pancreatic cancer cell proliferation and epithelial-to-mesenchymal transition–mediated metastasis by targeting ST7L. However, it is uncertain whether miR-331-3p is involved in drug resistance. Methods: We investigated the relationship between miR-331-3p and pancreatic cancer drug resistance. As part of this, microRNA mimics or inhibitors were transfected into pancreatic cancer cells. Quantitative polymerase chain reaction was used to detect miR-331-3p expression, and flow cytometry was used to detect cell apoptosis. The Cell Counting Kit-8 assay was used to measure the IC50 values of gemcitabine in pancreatic cancer cells. The expression of multidrug resistance protein 1, multidrug resistance-related protein 1, breast cancer resistance protein, β-Catenin, c-Myc, Cyclin D1, Bcl-2, and Caspase-3 was evaluated by Western blotting. Results: We confirmed that miR-331-3p is upregulated in gemcitabine-treated pancreatic cancer cells and plasma from chemotherapy patients. We also confirmed that miR-331-3p inhibition decreased drug resistance by regulating cell apoptosis and multidrug resistance protein 1, multidrug resistance-related protein 1, and breast cancer resistance protein expression in pancreatic cancer cells, whereas miR-331-3p overexpression had the opposite effect. We further demonstrated that miR-331-3p effects in drug resistance were partially reversed by ST7L overexpression. In addition, overexpression of miR-331-3p activated Wnt/β-catenin signaling in pancreatic cancer cells, and ST7L overexpression restored activation of Wnt/β-catenin signaling. Conclusions: Taken together, our data demonstrate that miR-331-3p contributes to drug resistance by activating Wnt/β-catenin signaling via ST7L in pancreatic cancer cells. These data provide a theoretical basis for new targeted therapies in the future.

Osteosarcoma is the most common primary malignant bone tumor in the clinic. It is more common in children and adolescents. It has high malignancy, early metastasis rate, rapid disease progression, and high mortality. Although past years have witnessed the great improvement in the treatments of osteosarcoma, there remains a long way to go. MicroRNAs affect the malignant biological behaviors such as tumor proliferation and metastasis by regulating their target genes. In this study, we investigated the role and mechanism of miR-384 in osteosarcoma. Quantitative real-time polymerase chain reaction assay was performed to detect the expression of miR-384 and insulin-like growth factor binding protein 3 in osteosarcoma tissues and cell lines and established its correlation with osteosarcoma tumor progression and metastasis. To probe whether miR-384 played a tumor suppression role in osteosarcoma, we carried out gain-of-function and loss-of-function assays. Cell Counting Kit-8, cell colony formation, and transwell assays were carried out to determine the cells proliferation and invasion, respectively. Western blot was used to detect the changes of epithelial–mesenchymal transition marker proteins and insulin-like growth factor binding protein 3. MiR-384 was downregulated in osteosarcoma tissues and cell lines. MiR-384 was overexpressed in G292 cells transfected with miR-384 mimics and knocked down in Saos-2 cells with small hairpin RNA targeting miR-384. Ectopic expression of miR-384 inhibited osteosarcoma cell proliferation, colony formation, and invasion. E-cadherin was brought to a decrease whereas N-cadherin and Snail to an increase under the silent expression of miR-384, while overexpression of miR-384 led to an opposite result. MiR-384 could regulate insulin-like growth factor binding protein 3 expression in osteosarcoma. Quantitative polymerase chain reaction and Western blotting results validated that miR-384 knockdown downgrades both messenger RNA and protein levels of insulin-like growth factor binding protein 3 in G292 cells, while miR-384 upregulation exerted an opposite effect in Saos-2 cells. Insulin-like growth factor binding protein 3 was upregulated in osteosarcoma tissues and osteosarcoma cell lines compared with normal ones. Through the bioinformatics database found that the upstream transcriptional regulator of insulin-like growth factor binding protein 3 is MECP2. So miR-384 can directly inhibit MECP2 and then promote the expression of insulin-like growth factor binding protein 3. These results suggested that miR-384 might be a potential therapeutic targets and biomarker in osteosarcoma.